AWS Professional Services has announced a transformation of its consulting model by introducing specialized agentic AI-powered consulting services to reduce cloud project timelines.

In a new "agent-first" approach, Amazon Web Services (AWS) is set to embed AI agents throughout the consulting lifecycle, alongside human experts, to speed up processes and enterprise digital transformations.

In initial pilot projects, AWS claimed the agents were successful in reducing months of work to weeks on cloud migration projects.

Francessca Vasquez, VP of professional services and agentic AI for AWS, said: “We believe in a future where intelligent agents work alongside expert consultants to compress development timelines, elevate solution quality, and enable organizations to achieve their digital transformation goals faster. Making this vision real requires a fundamental reimagining of the traditional consulting model.”

The AI-powered agents were designed to help teams navigate AWS services, cloud architecture decisions, and implementation guidance while drawing from its extensive experience and thousands of customer engagements.

The Core Agent System includes an agent specialized in cloud migration, capable of analyzing the statement of work alongside project artifacts, and then automating wave planning, dependency mapping, workload scheduling, and runbook generation.

"[The] consultant maintains strategic oversight while agents compress the timeline to just a few months, all while maintaining rigorous security and compliance standards," claimed Vasquez.

By combining existing AWS expertise with AI capabilities, the company will allow teams to access AWS best practices and operational knowledge more efficiently than before.

As another example, the AWS Professional Services Delivery Agent is set to use requirements such as notes, diagrams, and documentation to quickly produce design specifications, generate code, automate testing, and prepare deployment packages.

NFL scoring business transformation with agents

AWS says that organizations from various industries have already seen results by partnering with AWS ProServe agents, from rapid AI application development to accelerated cloud migrations.

For instance, the American National Football League (NFL) faced a challenge building agents to serve millions of fantasy football fans while maintaining speed and reliability. The organization partnered with the AWS Professional Services team, using the delivery agent to deploy a production-quality prototype that integrates next-gen stats, player news, weather data, and both proprietary and public NFL information to generate personalized fantasy football recommendations in a few days.

Mike Band, senior manager, research and analytics at the NFL, said: “We went from zero to production in eight weeks while maintaining the quality standards NFL fans expect. The framework automated routine development tasks, freeing our team to focus on performance optimization and delivering unique insights powered by NFL’s proprietary data.”

The agent system was built with enterprise-grade AWS technologies, including Amazon Bedrock AgentCore, AWS Transform, and advanced development tools like Kiro and Amazon Q Developer CLI to ensure security and scalability.

AI agents have seen growing popularity in various industries. Recently, IBM released an autonomous network solution for telecoms and enterprise networks to tackle the complexity of modern networks, where teams struggle to manage tools and manual processes.

IBM claims agentic AI can spot issues missed by other software tools, while tracing root causes across network layers and accelerating remediation. The vendor hopes this can provide clear visibility and a drop in escalations without parsing event logs and switching through various tools.

Amid the widespread enthusiasm around agents, a recent Gartner report, however, disputed the mantra that "the future is agentic," predicting that more than 40% of agentic AI projects will be canceled by the end of 2027 amid escalating costs, unclear business value, or inadequate risk controls.